Zero-shot Learning - Groups

SUN Attribute

The dataset used in the paper is SUN Attribute, which consists of 717 classes of images with annotations.

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Random Word Data Augmentation for Zero-Shot Anomaly Detection

This paper presents a novel method that leverages a visual-language model, CLIP, as a data source for zero-shot anomaly detection.

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Zero-Shot Automatic Pronunciation Assessment

Automatic Pronunciation Assessment (APA) is vital for computer-assisted language learning. Prior methods rely on annotated speech-text data to train Automatic Speech Recognition...

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Zero-1-to-3: Zero-shot one image to 3D object

Zero-shot one image to 3D object.

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Zero-Shot Temporal Action Detection via Vision-Language Prompting

Zero-Shot Temporal Action Detection via Vision-Language Prompting (STALE) model for the under-studied yet practically useful zero-shot temporal action detection (ZS-TAD)

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25 public datasets

The dataset used for evaluation of the MS-CLIP model, which consists of 25 public datasets for zero-shot learning and linear probing.

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Class Representative Learning Model

The CRL model is based on class-level classiﬁers, built class-by-class, that would be a representative of instances of a speciﬁc class by utilizing activation features of...

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M10

The paper discusses the use of multi-objective Bayesian optimization for hyperparameter transfer in topic models.

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Google Open Images

Google Open Images dataset, which contains 19,958 categories and is used for zero-shot learning.

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GeneCIS

GeneCIS is a benchmark for Compositional Image Retrieval, which aims to retrieve the relevant target image in a database.

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CIRCO

CIRCO is a benchmark for Compositional Image Retrieval, which aims to retrieve the relevant target image in a database.

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Vision-by-Language for Training-Free Compositional Image Retrieval

Compositional Image Retrieval through Vision-by-Language (CIReVL) is a training-free approach for Zero-Shot Compositional Image Retrieval (CIR). Utilizing off-the-shelf...

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ODIN: On-demand Data Formulation to Mitigate Dataset Lock-in

ODIN is an innovative approach that addresses the problem of dataset constraints by integrating generative AI models.

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AWA2

AWA2 is an animal dataset containing 37,322 images from 50 classes, with 85 attributes provided by experts to describe the semantic feature of each class.

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CIRR

CIRR is a general image dataset that comprises 36,554 triplets derived from 21,552 images from the popular natural language inference dataset NLVR2.

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FashionIQ

The FashionIQ dataset contains images of fashion products over 3 categories: Dress, Toptee, and Shirt, with 46,609 images in the training and 31,075 images in the validation set.

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Imagenette Dataset

The Imagenette dataset is a zero-shot image classification dataset, containing 13,394 images from ten easily separable classes in ImageNet.

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C-GQA

The C-GQA dataset is a large-scale dataset for compositional zero-shot learning, containing 413 attributes and 674 objects.

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CLEVR

CLEVR images contain objects characterized by a set of attributes (shape, color, size and material). The questions are grouped into 5 categories: Exist, Count, CompareInteger,...

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MeaCap: Memory-Augmented Zero-shot Image Captioning

Zero-shot image captioning without well-paired image-text data can be divided into two categories, training-free and text-only-training. Generally, these two types of methods...

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20 datasets found